Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model

Neuroglobin regulates autophagy through mTORC1/RAPTOR/ULK-1 pathway in human neuroblastoma cells

Neuroglobin (NGB) is a hexacoordinated hemeprotein mainly expressed in neurons. Following its upregulation and mitochondrial localization, NGB plays a pro-survival role against neuronal stress. Previously, we built a stable NGB-FLAG-overexpressing neuroblastoma cell line and showed that NGB promotes autophagy and localizes in autophagolysosomes. Here we studied the interactome of NGB-FLAG cells to identify novel autophagy-related NGB-binding partners and investigate how its upregulation could induce autophagy. LC3-II and p62 levels as well as mTORC1 activity were analyzed to evaluate autophagy in NGB-FLAG cells. NGB interactors were identified by affinity purification-mass spectrometry and protein-protein interaction network analysis and validated by immunoprecipitation. The increase of LC3-II and decrease of p62 in NGB-FLAG compared to control confirmed that NGB overexpression promotes autophagy. Interactome analysis identified the Regulatory associated protein of mTOR (RPTOR) as one of 134 putative NGB interactors, further validated by immunoprecipitation. NGB overexpression also determined a consistent increment of RPTOR phosphorylation at Ser792 which is required for mTORC1 inhibition, then confirmed by lower levels of phospho-mTOR and phospho-ULK1 in NGB-FLAG compared to control. Collectively, our data suggests that NGB is a positive regulator of autophagy. Through association with RPTOR, NGB may promote its activation and inhibit mTORC1 repressive activity on autophagy initiation.

Cross-Linking Mass Spectrometry to Capture Protein Network Dynamics of Cell Membranome

Interactions among proteins are fundamental in driving functions and activities that regulate cell biology, mechanotransduction, and cell-to-cell communication/recognition. Recently, cross-linking mass spectrometry (XL-MS) has emerged as a powerful tool for interaction discovery and characterization, driving the enlightenment of novel binding partners otherwise undetected. Covalent linkages of two amino acid residues of proteins (or within complexes) in close proximity can be identified by MS, thus providing structural insights such as distance restraints or unraveling interaction dynamics.The XL-MS workflow described here is applied to map the plasma membrane protein (PMP) networks since they play important roles in the modulation of diverse molecular processes, including transport, signal transduction, endocytosis, and secretion. The strategy includes cross-linking of PMP-enriched fractions, label-free nanoLC-MS/MS, and bioinformatics data analysis. "Membranome" interconnections constitute around 30% of the mammalian proteome and 60% of all drug targets. Exploring such networks under different biological conditions is a promising and unbiased approach to depicting regulatory pathways that govern cell behavior.

Unraveling the impact of different liposomal formulations on the plasma protein corona composition might give hints on the targeting capability of nanoparticles

Nanoparticles (NPs) interact with biological fluids after being injected into the bloodstream. The interactions between NPs and plasma proteins at the nano-bio interface affect their biopharmaceutical properties and distribution in the organ and tissues due to protein corona (PrC) composition, and in turn, modification of the resulting targeting capability. Moreover, lipid and polymer NPs, at their interface, affect the composition of PrC and the relative adsorption and abundance of specific proteins. To investigate this latter aspect, we synthesized and characterized different liposomal formulations (LFs) with lipids and polymer-conjugated lipids at different molar ratios, having different sizes, size distributions and surface charges. The PrC composition of various designed LFs was evaluated ex vivo in human plasma by label-free quantitative proteomics. We also correlated the relative abundance of identified specific proteins in the coronas of the different LFs with their physicochemical properties (size, PDI, zeta potential). The evaluation of outputs from different bioinformatic tools discovered protein clusters allowing to highlight: (i) common as well as the unique species for the various formulations; (ii) correlation between each identified PrC and the physicochemical properties of LFs; (iii) some preferential binding determined by physicochemical properties of LFs; (iv) occurrence of formulation-specific protein patterns in PrC. Investigating specific clusters in PrC will help decode the multivalent roles of the protein pattern components in the drug delivery process, taking advantage of the bio-nanoscale recognition and identification for significant advances in nanomedicine.

Methylmalonic acidemia triggers lysosomal-autophagy dysfunctions

BACKGROUND

Methylmalonic acidemia (MMA) is a rare inborn error of propionate metabolism caused by deficiency of the mitochondrial methylmalonyl-CoA mutase (MUT) enzyme. As matter of fact, MMA patients manifest impairment of the primary metabolic network with profound damages that involve several cell components, many of which have not been discovered yet. We employed cellular models and patients-derived fibroblasts to refine and uncover new pathologic mechanisms connected with MUT deficiency through the combination of multi-proteomics and bioinformatics approaches.

RESULTS

Our data show that MUT deficiency is connected with profound proteome dysregulations, revealing molecular actors involved in lysosome and autophagy functioning. To elucidate the effects of defective MUT on lysosomal and autophagy regulation, we analyzed the morphology and functionality of MMA-lysosomes that showed deep alterations, thus corroborating omics data. Lysosomes of MMA cells present as enlarged vacuoles with low degradative capabilities. Notwithstanding, treatment with an anti-propionigenic drug is capable of totally rescuing lysosomal morphology and functional activity in MUT-deficient cells. These results indicate a strict connection between MUT deficiency and lysosomal-autophagy dysfunction, providing promising therapeutic perspectives for MMA.

CONCLUSIONS

Defective homeostatic mechanisms in the regulation of autophagy and lysosome functions have been demonstrated in MUT-deficient cells. Our data prove that MMA triggers such dysfunctions impacting on autophagosome-lysosome fusion and lysosomal activity.

Protein interaction networks characterizing the A549 cells Klotho transfected are associated with activated pro-apoptotic Bim and suppressed Wnt/β-catenin signaling pathway

Invasive assays and lung tumor-bearing mice models using a human lung adenocarcinoma cell line A549 cells transfected with the Klotho (KL) gene, A549/KL cells, have confirmed that KL suppresses invasive/metastatic potential. This study aimed to identify the co-expression protein networks and proteomic profiles associated with A549/KL cells to understand how Klotho protein expression affects molecular networks associated with lung carcinoma malignancy. A two-step application of a weighted network correlation analysis to the cells' quantitative proteome datasets of a total of 6,994 proteins, identified by mass spectrometry-based proteomic analysis with data-independent acquisition (DIA), identified one network module as most significantly associated with the A549/KL trait. Upstream analyses, confirmed by western blot, implicated the pro-apoptotic Bim (Bcl-2-like protein 11) as a master regulator of molecular networks affected by Klotho. GeneMANIA interaction networks and quantitative proteome data implicated that Klotho interacts with two signaling axes: negatively with the Wnt/β-catenin axis, and positively by activating Bim. Our findings might contribute to the development of future therapeutic strategies.

Proteomics and Metabolomics in Biomedicine

The technological advances of recent years have significantly enhanced medical discoveries [...].

Unravelling a novel role for cannabidivarin in the modulation of subventricular zone postnatal neurogenesis

Postnatal neurogenesis has been shown to rely on the endocannabinoid system. Here we aimed at unravelling the role of Cannabidivarin (CBDV), a non-psychoactive cannabinoid, with high affinity for the non-classical cannabinoid receptor TRPV1, on subventricular zone (SVZ) postnatal neurogenesis. Using the neurosphere assay, SVZ-derived neural stem/progenitor cells (NSPCs) were incubated with CBDV and/or 5'-Iodoresinferotoxin (TRPV1 antagonist), and their role on cell viability, proliferation, and differentiation were dissected. CBDV was able to promote, through a TRPV1-dependent mechanism, cell survival, cell proliferation and neuronal differentiation. Furthermore, pulse-chase experiments revealed that CBDV-induced neuronal differentiation was a result of cell cycle exit of NSPCs. Regarding oligodendrocyte differentiation, CBDV inhibited oligodendrocyte differentiation and maturation. Since our data suggested that the CBDV-induced modulation of NSPCs acted via TRPV1, a sodium-calcium channel, and that intracellular calcium levels are known regulators of NSPCs fate and neuronal maturation, single cell calcium imaging was performed to evaluate the functional response of SVZ-derived cells. We observed that CBDV-responsive cells displayed a two-phase calcium influx profile, being the initial phase dependent on TRPV1 activation. Taken together, this work unveiled a novel and untapped neurogenic potential of CBDV via TRPV1 modulation. These findings pave the way to future neural stem cell biological studies and repair strategies by repurposing this non-psychoactive cannabinoid as a valuable therapeutic target.

Targeted lipidomics data of COVID-19 patients

The dataset provided with this article describes a targeted lipidomics analysis performed on the serum of COVID-19 patients characterized by different degree of severity. As the ongoing pandemic has posed a challenging threat for humanity, the data here presented belong to one of the first lipidomics studies carried out on COVID-19 patients’ samples collected during the first pandemic waves. Serum samples were obtained from hospitalized patients with a molecular diagnosis of SARS-CoV-2 infection detected after nasal swab, and categorized as mild, moderate, or severe according to pre-established clinical descriptors. The MS-based targeted lipidomic analysis was performed by MRM using a Triple Quad 5500+ mass spectrometer, and the quantitative data were acquired on a panel of 483 lipids. The characterization of this lipidomic dataset has been outlined using multivariate and univariate descriptive statistics and bioinformatics tools.

Bottom-Up Proteomics: Advancements in Sample Preparation

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation.

Lipidomic alterations in human saliva from cystic fibrosis patients

Cystic fibrosis is a hereditary metabolic disorder characterized by impaired traffic of chloride ions and water through membranes of the respiratory and gastrointestinal, that causes inadequate hydration of airway surfaces, dehydrated mucous secretions and a high-sodium chloride sweat. Although the classical presentation of the condition is well known, a better characterization of metabolic alterations related is need. In particular, the metabolic composition alterations of biological fluids may be influence by the disease state and could be captured as putative signature to set targeted therapeutic strategies. A targeted comprehensive mass spectrometry-based platform was employed to dissect the lipid content of saliva samples form CF patients, in order to investigate alterations in the lipid metabolic homeostasis related to the pathology, chronic obstructive pulmonary disease, Pseudomonas Aeruginosa infection, pancreatic insufficiency, liver disfunction and diabetes-related complications.

Sex-Gender-Based Differences in Metabolic Diseases

Sexual dimorphism creates different biological and cellular activities and selective regulation mechanisms in males and females, thus generating differential responses in health and disease. In this scenario, the sex itself is a source of physiologic metabolic disparities that depend on constitutive genetic and epigenetic features that characterize in a specific manner one sex or the other. This has as a direct consequence a huge impact on the metabolic routes that drive the phenotype of an individual. The impact of sex is being clearly recognized also in disease, whereas male and females are more prone to the development of some disorders, or have selective responses to drugs and therapeutic treatments. Actually, very less is known regarding the probable differences guided by sex in the context of inherited metabolic disorders, owing to the scarce consideration of sex in such restricted field, accompanied by an intrinsic bias connected with the rarity of such diseases. Metabolomics technologies have been ultimately developed and adopted for being excellent tools for the investigation of metabolic mechanisms, for marker discovery or monitoring, and for supporting diagnostic procedures of metabolic disorders. Hence, metabolomic approaches can excellently embrace the discovery of sex differences, especially when associated to the outcome or the management of certain inborn errors of the metabolism.

Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era

The majority of processes that occur in daily cell life are modulated by hundreds to thousands of dynamic protein-protein interactions (PPI). The resulting protein complexes constitute a tangled network that, with its continuous remodeling, builds up highly organized functional units. Thus, defining the dynamic interactome of one or more proteins allows determining the full range of biological activities these proteins are capable of. This conceptual approach is poised to gain further traction and significance in the current postgenomic era wherein the treatment of severe diseases needs to be tackled at both genomic and PPI levels. This also holds true for COVID-19, a multisystemic disease affecting biological networks across the biological hierarchy from genome to proteome to metabolome. In this overarching context and the current historical moment of the COVID-19 pandemic where systems biology increasingly comes to the fore, cross-linking mass spectrometry (XL-MS) has become highly relevant, emerging as a powerful tool for PPI discovery and characterization. This expert review highlights the advanced XL-MS approaches that provide in vivo insights into the three-dimensional protein complexes, overcoming the static nature of common interactomics data and embracing the dynamics of the cell proteome landscape. Many XL-MS applications based on the use of diverse cross-linkers, MS detection methods, and predictive bioinformatic tools for single proteins or proteome-wide interactions were shown. We conclude with a future outlook on XL-MS applications in the field of structural proteomics and ways to sustain the remarkable flexibility of XL-MS for dynamic interactomics and structural studies in systems biology and planetary health.

A review of suspension trapping digestion method in bottom-up proteomics

The standard bottom-up proteomic workflow is comprised of sample preparation, data acquisition, and data analysis. While the latter two parts have made considerable advances in the last decade, sample preparation has remained an important challenge within the workflow due to the multi-step nature of complex biological samples, and still requires much development. Several sample preparation methods have been developed and used in the last two decades, including in-gel, in-solution, on-bead, filter-aided sample preparation, and suspension trapping, to improve reproducibility, efficiency, scalability, and reduce handling time of this process. One of the most recent methods developed and applied in proteomics studies in recent years is suspension trapping, which combines rapid detergent removal, reactor-type protein digestion, and peptide clean-up in a tip or spin column. Suspension trapping is a simple, rapid, and reproducible digestion method that can effectively handle proteins in low microgram or sub-microgram amounts. This review discusses the benefits of the suspension trapping digestion method in relation to its development and application in bottom-up proteomics studies. We also discuss recent applications of suspension trapping digestion to different sample types and the features of the suspension trapping digestion method compared with other sample preparation methods. This article is protected by copyright. All rights reserved.

Sex differences in the human metabolome

BACKGROUND

The sexual dimorphism represents one of the triggers of the metabolic disparities between the organisms, advising about wild implications in research or diagnostics contexts. Despite the mounting recognition of the importance of sex consideration in the biomedical fields, the identification of male- and female-specific metabolic signatures has not been achieved.

MAIN BODY

This review pointed the focus on the metabolic differences related to the sex, evidenced by metabolomics studies performed on healthy populations, with the leading aim of understanding how the sex influences the baseline metabolome. The main shared signatures and the apparent dissimilarities between males and females were extracted and highlighted from the metabolome of the most commonly analyzed biological fluids, such as serum, plasma, and urine. Furthermore, the influence of age and the significant interactions between sex and age have been taken into account.

CONCLUSIONS

The recognition of sex patterns in human metabolomics has been defined in diverse biofluids. The detection of sex- and age-related differences in the metabolome of healthy individuals are helpful for translational applications from the bench to the bedside to set targeted diagnostic and prevention approaches in the context of personalized medicine.

Intravital Imaging with Two-Photon Microscopy: A Look into the Kidney

Fluorescence microscopy has represented a crucial technique to explore the cellular and molecular mechanisms in the field of biomedicine. However, the conventional one-photon microscopy exhibits many limitations when living samples are imaged. The new technologies, including two-photon microscopy (2PM), have considerably improved the in vivo study of pathophysiological processes, allowing the investigators to overcome the limits displayed by previous techniques. 2PM enables the real-time intravital imaging of the biological functions in different organs at cellular and subcellular resolution thanks to its improved laser penetration and less phototoxicity. The development of more sensitive detectors and long-wavelength fluorescent dyes as well as the implementation of semi-automatic software for data analysis allowed to gain insights in essential physiological functions, expanding the frontiers of cellular and molecular imaging. The future applications of 2PM are promising to push the intravital microscopy beyond the existing limits. In this review, we provide an overview of the current state-of-the-art methods of intravital microscopy, focusing on the most recent applications of 2PM in kidney physiology.

COVIDomics: The Proteomic and Metabolomic Signatures of COVID-19

Omics-based technologies have been largely adopted during this unprecedented global COVID-19 pandemic, allowing the scientific community to perform research on a large scale to understand the pathobiology of the SARS-CoV-2 infection and its replication into human cells. The application of omics techniques has been addressed to every level of application, from the detection of mutations, methods of diagnosis or monitoring, drug target discovery, and vaccine generation, to the basic definition of the pathophysiological processes and the biochemical mechanisms behind the infection and spread of SARS-CoV-2. Thus, the term COVIDomics wants to include those efforts provided by omics-scale investigations with application to the current COVID-19 research. This review summarizes the diverse pieces of knowledge acquired with the application of COVIDomics techniques, with the main focus on proteomics and metabolomics studies, in order to capture a common signature in terms of proteins, metabolites, and pathways dysregulated in COVID-19 disease. Exploring the multiomics perspective and the concurrent data integration may provide new suitable therapeutic solutions to combat the COVID-19 pandemic.

Overexpression of Neuroglobin Promotes Energy Metabolism and Autophagy Induction in Human Neuroblastoma SH-SY5Y Cells

Neuroglobin (NGB) is an O₂-binding globin mainly expressed in the central and peripheral nervous systems and cerebrospinal fluid. Previously, it was demonstrated that NGB overexpression protects cells from hypoxia-induced death. To investigate processes promoted by NGB overexpression, we used a cellular model of neuroblastoma stably overexpressing an NGB-FLAG construct. We used a proteomic approach to identify the specific profile following NGB overexpression. To evaluate the role of NGB overexpression in increasing energetic metabolism, we measured oxygen consumption rate (OCR) and the extracellular acidification rate through Seahorse XF technology. The effect on autophagy induction was evaluated by analyzing SQSTM1/p62 and LC3-II expression. Proteomic analysis revealed several differentially regulated proteins, involved in oxidative phosphorylation and integral mitochondrial proteins linked to energy metabolism. The analysis of mitochondrial metabolism demonstrated that NGB overexpression increases mitochondrial ATP production. Indeed, NGB overexpression enhances bioenergetic metabolism, increasing OCR and oxygen consumption. Analysis of autophagy induction revealed an increase of LC3-II together with a significant decrease of SQSTM1/p62, and NGB-LC3-II association during autophagosome formation. These results highlight the active participation of NGB in several cellular processes that can be upregulated in response to NGB overexpression, playing a role in the adaptive response to stress in neuroblastoma cells.

The Serum Metabolome of Moderate and Severe COVID-19 Patients Reflects Possible Liver Alterations Involving Carbon and Nitrogen Metabolism

COVID-19 is a global threat that has spread since the end of 2019, causing severe clinical sequelae and deaths, in the context of a world pandemic. The infection of the highly pathogenetic and infectious SARS-CoV-2 coronavirus has been proven to exert systemic effects impacting the metabolism. Yet, the metabolic pathways involved in the pathophysiology and progression of COVID-19 are still unclear. Here, we present the results of a mass spectrometry-based targeted metabolomic analysis on a cohort of 52 hospitalized COVID-19 patients, classified according to disease severity as mild, moderate, and severe. Our analysis defines a clear signature of COVID-19 that includes increased serum levels of lactic acid in all the forms of the disease. Pathway analysis revealed dysregulation of energy production and amino acid metabolism. Globally, the variations found in the serum metabolome of COVID-19 patients may reflect a more complex systemic perturbation induced by SARS-CoV-2, possibly affecting carbon and nitrogen liver metabolism.

Proteomic and Bioinformatic Investigation of Altered Pathways in Neuroglobin-Deficient Breast Cancer Cells

Neuroglobin (NGB) is a myoglobin-like monomeric globin that is involved in several processes, displaying a pivotal redox-dependent protective role in neuronal and extra-neuronal cells. NGB remarkably exerts its function upon upregulation by NGB inducers, such as 17β-estradiol (E2) and H₂O₂. However, the molecular bases of NGB’s functions remain undefined, mainly in non-neuronal cancer cells. Human MCF-7 breast cancer cells with a knocked-out (KO) NGB gene obtained using CRISPR/Cas9 technology were analyzed using shotgun label-free quantitative proteomics in comparison with control cells. The differential proteomics experiments were also performed after treatment with E2, H₂O₂, and E2 + H₂O₂. All the runs acquired using liquid chromatography–tandem mass spectrometry were elaborated within the same MaxQuant analysis, leading to the quantification of 1872 proteins in the global proteomic dataset. Then, a differentially regulated protein dataset was obtained for each specific treatment. After the proteomic study, multiple bioinformatics analyses were performed to highlight unbalanced pathways and processes. Here, we report the proteomic and bioinformatic investigations concerning the effects on cellular processes of NGB deficiency and cell treatments. Globally, the main processes that were affected were related to the response to stress, cytoskeleton dynamics, apoptosis, and mitochondria-driven pathways.